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    ⋆This paper has been handled by associate editor Tony Sze.The application of novel connected vehicles emulated data on real-time crash potential prediction for arterials

    Li, Pei / Abdel-Aty, Mohamed / Cai, Qing et al. | Elsevier | 2020
    Schlagwörter: Deep learning

    2D-supervised fast neural fluid reconstruction technique for time-resolved volumetric flame reconstruction

    Zhang, Fuhao / Zhang, Weixuan / Gong, Shuicheng et al. | Elsevier | 2023
    Schlagwörter: Deep learning

    4D flight trajectory prediction using a hybrid Deep Learning prediction method based on ADS-B technology: A case study of Hartsfield–Jackson Atlanta International Airport (ATL)

    Shafienya, Hesam / Regan, Amelia C. | Elsevier | 2022
    Schlagwörter: Deep learning

    A Bayesian approach to quantifying uncertainties and improving generalizability in traffic prediction models

    Sengupta, Agnimitra / Mondal, Sudeepta / Das, Adway et al. | Elsevier | 2024
    Schlagwörter: Deep learning

    A Bayesian deep learning method for freeway incident detection with uncertainty quantification

    Liu, Genwang / Jin, Haolin / Li, Jiaze et al. | Elsevier | 2022
    Schlagwörter: Bayesian deep learning

    A convolutional neural network method to improve efficiency and visualization in modeling driver’s visual field on roads using MLS data

    Ma, Yang / Zheng, Yubing / Cheng, Jianchuan et al. | Elsevier | 2019
    Schlagwörter: Deep learning

    A critical review on the state-of-the-art and future prospects of machine learning for Earth observation operations

    Miralles, Pablo / Thangavel, Kathiravan / Fulvio Scannapieco, Antonio et al. | Elsevier | 2023
    Schlagwörter: Deep Learning

    A customized deep learning approach to integrate network-scale online traffic data imputation and prediction

    Zhang, Zhengchao / Lin, Xi / Li, Meng et al. | Elsevier | 2021
    Schlagwörter: Deep learning

    AdapGL: An adaptive graph learning algorithm for traffic prediction based on spatiotemporal neural networks

    Zhang, Wei / Zhu, Fenghua / Lv, Yisheng et al. | Elsevier | 2022
    Schlagwörter: Deep learning

    Addressing COVID-induced changes in spatiotemporal travel mobility and community structure utilizing trip data: An innovative graph-based deep learning approach

    Chang, Ximing / Wu, Jianjun / Yu, Jiarui et al. | Elsevier | 2024
    Schlagwörter: Deep learning

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